Identification of unit overlap regions for concatenative speech synthesis system
First Claim
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1. A method for identifying a unit overlap region for concatenative speech synthesis, comprising:
- defining a statistical model for representing time-varying properties of speech;
providing a plurality of time-series data corresponding to different sound units containing the same vowel;
extracting speech signal parameters from said time-series data and using said parameters to train said statistical model;
using said trained statistical model to identify a recurring sequence in said time-series data and associating said recurring sequence with a nuclear trajectory region of said vowel;
using said recurring sequence to delimit the unit overlap region for concatenative speech synthesis.
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Abstract
Speech signal parameters are extracted from time-series data corresponding to different sound units containing the same vowel. The extracted parameters are used to train a statistical model, such as a Hidden Markov-based Model, that has a data structure for separately modeling the nuclear trajectory region of the vowel and its surrounding transition elements. The model is trained as through embedded re-estimation to automatically determine optimally aligned models that identify the nuclear trajectory region. The boundaries of the nuclear trajectory region serve to delimit the overlap region for subsequent sound unit concatenation.
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Citations
15 Claims
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1. A method for identifying a unit overlap region for concatenative speech synthesis, comprising:
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defining a statistical model for representing time-varying properties of speech;
providing a plurality of time-series data corresponding to different sound units containing the same vowel;
extracting speech signal parameters from said time-series data and using said parameters to train said statistical model;
using said trained statistical model to identify a recurring sequence in said time-series data and associating said recurring sequence with a nuclear trajectory region of said vowel;
using said recurring sequence to delimit the unit overlap region for concatenative speech synthesis. - View Dependent Claims (2, 3, 4, 5, 6, 7)
using said data structure to discard a portion of said time-series data corresponding to one of said first and second transition elements.
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8. A method for performing concatenative speech synthesis, comprising:
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defining a statistical model for representing time-varying properties of speech;
providing a plurality of time-series data corresponding to different sound units containing the same vowel;
extracting speech signal parameters from said time-series data and using said parameters to train said statistical model;
using said trained statistical model to identify a recurring sequence in said time-series data and associating said recurring sequence with a nuclear trajectory region of said vowel;
using said recurring sequence to delimit a unit overlap region for each of said sound units;
concatenatively synthesizing a new sound unit by overlapping and merging said time-series data from two of said different sound units based on the respective unit overlap region of said sound units. - View Dependent Claims (9, 10, 11, 12, 13, 14, 15)
using said data structure to discard a portion of said time-series data corresponding to one of said first and second transition elements.
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Specification